Palabras clave
Inteligencia artificial
Educación médica
Enseñanza de la semiología
Tecnología en medicina
Modelos de lenguaje de gran tamaño
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Resumen
Objetivo: Evaluar la fiabilidad y el rendimiento de las herramientas actuales de inteligencia artificial (IA) que utilizan grandes modelos de lenguaje para describir signos y síntomas en semiología médica y compararlos entre sí. Métodos: Se seleccionaron descriptores comunes en la práctica médica y la enseñanza de la semiología médica, que abarcan los principales sistemas corporales, como los sistemas cardiovascular, respiratorio, digestivo y neurológico. Se utilizaron modelos de lenguaje gratuitos y ampliamente utilizados, como Chat GPT (GPT-4), Gemini 1.5 y Microsoft Copilot, para las consultas mediante el comando "Definir [término]". Las respuestas se evaluaron como inexistentes, incompletas o completas, comparándolas con la literatura especializada. Los casos cuestionables fueron revisados por un tercer observador. Resultados: De las 300 consultas realizadas, el 56,4 % se consideraron completas. El sistema respiratorio mostró la mayor precisión (87,5 %). El asistente virtual de inteligencia artificial Copilot destacó con un 60 % de respuestas completas. Conclusión: La IA ha demostrado potencial en el aprendizaje de la semiología médica, aunque necesita mejoras para lograr una mayor precisión.
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